Adaptive Critic Design-Based Dynamic Stochastic Optimal Control Design for a Microgrid With Multiple Renewable Resources

This paper proposes a three-layer optimization and an intelligent control algorithm for a microgrid with multiple renewable resources. A dual heuristic dynamic programming-based system control layer is used to ensure the dynamic performance and voltage dynamics of the microgrid as the system operation conditions change. A local layer maximizes the capability of the photovoltaic (PV) wind power generators and battery systems, and a model predictive control-based device layer increases the tracking accuracy of the converter control. The proposed control scheme, system wide adaptive predictive supervisory control (SWAPSC) smooths the output of PV and wind generators under intermittencies, maintains bus voltage by providing dynamic reactive power support to the grid, and reduces the total system losses while minimizing degradation of battery life span. Performance comparisons are made with and without SWAPSC for an IEEE 13 node test system with a PV farm, a wind farm, and two battery-based energy storage systems.